Apple Inc.

∙ Cupertino , United States ∙ 0 followers

Apple Inc. is an American multinational technology company headquartered in Cupertino, California, that designs, develops, and sells consumer electronics, computer software, and online services.

Set Distribution Networks: a Generative Model for Sets of Images

Images with shared characteristics naturally form sets. For example, in ...
06/18/2020 ∙ by Shuangfei Zhai, et al. ∙ 31 ∙ share

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Least squares binary quantization of neural networks

Quantizing weights and activations of deep neural networks results in si...
01/09/2020 ∙ by Hadi Pouransari, et al. ∙ 27 ∙ share

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Geometric Capsule Autoencoders for 3D Point Clouds

We propose a method to learn object representations from 3D point clouds...
12/06/2019 ∙ by Nitish Srivastava, et al. ∙ 21 ∙ share

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Worst Cases Policy Gradients

Recent advances in deep reinforcement learning have demonstrated the cap...
11/09/2019 ∙ by Yichuan Charlie Tang, et al. ∙ 20 ∙ share

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Democratizing Production-Scale Distributed Deep Learning

The interest and demand for training deep neural networks have been expe...
10/31/2018 ∙ by Minghuang Ma, et al. ∙ 12 ∙ share

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One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment

PointNet has recently emerged as a popular representation for unstructur...
12/12/2019 ∙ by Vinit Sarode, et al. ∙ 12 ∙ share

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Unsupervised Style and Content Separation by Minimizing Mutual Information for Speech Synthesis

We present a method to generate speech from input text and a style vecto...
03/09/2020 ∙ by Ting-yao Hu, et al. ∙ 12 ∙ share

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3D Manhattan Room Layout Reconstruction from a Single 360 Image

Recent approaches for predicting layouts from 360 panoramas produce exce...
10/09/2019 ∙ by Chuhang Zou, et al. ∙ 11 ∙ share

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MVX-Net: Multimodal VoxelNet for 3D Object Detection

Many recent works on 3D object detection have focused on designing neura...
04/02/2019 ∙ by Vishwanath A. Sindagi, et al. ∙ 10 ∙ share

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Non-Autoregressive Text Generation with Pre-trained Language Models

Non-autoregressive generation (NAG) has recently attracted great attenti...
02/16/2021 ∙ by Yixuan Su, et al. ∙ 10 ∙ share

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Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution

Knowledge distillation has been used to transfer knowledge learned by a ...
06/30/2020 ∙ by Hadi Pouransari, et al. ∙ 7 ∙ share

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Nonlinear Conjugate Gradients For Scaling Synchronous Distributed DNN Training

Nonlinear conjugate gradient (NLCG) based optimizers have shown superior...
12/07/2018 ∙ by Saurabh Adya, et al. ∙ 6 ∙ share

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Towards Learning Multi-agent Negotiations via Self-Play

Making sophisticated, robust, and safe sequential decisions is at the he...
01/28/2020 ∙ by Yichuan Charlie Tang, et al. ∙ 6 ∙ share

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Capsules with Inverted Dot-Product Attention Routing

We introduce a new routing algorithm for capsule networks, in which a ch...
02/12/2020 ∙ by Yao-Hung Hubert Tsai, et al. ∙ 5 ∙ share

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Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces

Word embedding techniques heavily rely on the abundance of training data...
11/12/2018 ∙ by Victor Prokhorov, et al. ∙ 2 ∙ share

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PCRNet: Point Cloud Registration Network using PointNet Encoding

PointNet has recently emerged as a popular representation for unstructur...
08/21/2019 ∙ by Vinit Sarode, et al. ∙ 1 ∙ share

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VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

Accurate detection of objects in 3D point clouds is a central problem in...
11/17/2017 ∙ by Yin Zhou, et al. ∙ 0 ∙ share

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Learning from Simulated and Unsupervised Images through Adversarial Training

With recent progress in graphics, it has become more tractable to train ...
12/22/2016 ∙ by Ashish Shrivastava, et al. ∙ 0 ∙ share

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Neural Belief Tracker: Data-Driven Dialogue State Tracking

One of the core components of modern spoken dialogue systems is the beli...
06/12/2016 ∙ by Nikola Mrkšić, et al. ∙ 0 ∙ share

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Actionable Email Intent Modeling with Reparametrized RNNs

Emails in the workplace are often intentional calls to action for its re...
12/26/2017 ∙ by Chu-Cheng Lin, et al. ∙ 0 ∙ share

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Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules

Morphologically rich languages accentuate two properties of distribution...
06/01/2017 ∙ by Ivan Vulić, et al. ∙ 0 ∙ share

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Counter-fitting Word Vectors to Linguistic Constraints

In this work, we present a novel counter-fitting method which injects an...
03/02/2016 ∙ by Nikola Mrkšić, et al. ∙ 0 ∙ share

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Global Pose Estimation with an Attention-based Recurrent Network

The ability for an agent to localize itself within an environment is cru...
02/19/2018 ∙ by Emilio Parisotto, et al. ∙ 0 ∙ share

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Divide, Denoise, and Defend against Adversarial Attacks

Deep neural networks, although shown to be a successful class of machine...
02/19/2018 ∙ by Seyed-Mohsen Moosavi-Dezfooli, et al. ∙ 0 ∙ share

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Structured Control Nets for Deep Reinforcement Learning

In recent years, Deep Reinforcement Learning has made impressive advance...
02/22/2018 ∙ by Mario Srouji, et al. ∙ 0 ∙ share

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Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching

Community-based question answering (CQA) websites represent an important...
04/22/2018 ∙ by Xiao Yang, et al. ∙ 0 ∙ share

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Learning Sharing Behaviors with Arbitrary Numbers of Agents

We propose a method for modeling and learning turn-taking behaviors for ...
12/10/2018 ∙ by Katherine Metcalf, et al. ∙ 0 ∙ share

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Mirroring to Build Trust in Digital Assistants

We describe experiments towards building a conversational digital assist...
04/02/2019 ∙ by Katherine Metcalf, et al. ∙ 0 ∙ share

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Differentiable Approximation Bridges For Training Networks Containing Non-Differentiable Functions

Modern neural network training relies on piece-wise (sub-)differentiable...
05/09/2019 ∙ by Jason Ramapuram, et al. ∙ 0 ∙ share

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Speaker-Independent Speech-Driven Visual Speech Synthesis using Domain-Adapted Acoustic Models

Speech-driven visual speech synthesis involves mapping features extracte...
05/15/2019 ∙ by Ahmed Hussen Abdelaziz, et al. ∙ 0 ∙ share

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On Modeling ASR Word Confidence

We present a new method for computing ASR word confidences that effectiv...
07/22/2019 ∙ by Woojay Jeon, et al. ∙ 0 ∙ share

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Density estimation in representation space to predict model uncertainty

Deep learning models frequently make incorrect predictions with high con...
08/20/2019 ∙ by Tiago Ramalho, et al. ∙ 0 ∙ share

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Connecting and Comparing Language Model Interpolation Techniques

In this work, we uncover a theoretical connection between two language m...
08/26/2019 ∙ by Ernest Pusateri, et al. ∙ 0 ∙ share

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Single Training Dimension Selection for Word Embedding with PCA

In this paper, we present a fast and reliable method based on PCA to sel...
08/30/2019 ∙ by Yu Wang, et al. ∙ 0 ∙ share

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Jointly Learning to Align and Translate with Transformer Models

The state of the art in machine translation (MT) is governed by neural a...
09/04/2019 ∙ by Sarthak Garg, et al. ∙ 0 ∙ share

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Neural Network-Based Modeling of Phonetic Durations

A deep neural network (DNN)-based model has been developed to predict no...
09/06/2019 ∙ by Xizi Wei, et al. ∙ 0 ∙ share

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Reverse Transfer Learning: Can Word Embeddings Trained for Different NLP Tasks Improve Neural Language Models?

Natural language processing (NLP) tasks tend to suffer from a paucity of...
09/09/2019 ∙ by Lyan Verwimp, et al. ∙ 0 ∙ share

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Modeling patterns of smartphone usage and their relationship to cognitive health

The ubiquity of smartphone usage in many people's lives make it a rich s...
11/13/2019 ∙ by Jonas Rauber, et al. ∙ 0 ∙ share

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An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering

To produce a domain-agnostic question answering model for the Machine Re...
12/04/2019 ∙ by Shayne Longpre, et al. ∙ 0 ∙ share

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Stochastic Weight Averaging in Parallel: Large-Batch Training that Generalizes Well

We propose Stochastic Weight Averaging in Parallel (SWAP), an algorithm ...
01/07/2020 ∙ by Vipul Gupta, et al. ∙ 0 ∙ share

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Voice trigger detection from LVCSR hypothesis lattices using bidirectional lattice recurrent neural networks

We propose a method to reduce false voice triggers of a speech-enabled p...
02/29/2020 ∙ by Woojay Jeon, et al. ∙ 0 ∙ share

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Speech Translation and the End-to-End Promise: Taking Stock of Where We Are

Over its three decade history, speech translation has experienced severa...
04/14/2020 ∙ by Matthias Sperber, et al. ∙ 0 ∙ share

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Question Rewriting for Conversational Question Answering

Conversational question answering (QA) requires answers conditioned on t...
04/30/2020 ∙ by Svitlana Vakulenko, et al. ∙ 0 ∙ share

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Self-supervised Learning of Visual Speech Features with Audiovisual Speech Enhancement

We present an introspection of an audiovisual speech enhancement model. ...
04/25/2020 ∙ by Zakaria Aldeneh, et al. ∙ 0 ∙ share

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Learning to Rank Intents in Voice Assistants

Voice Assistants aim to fulfill user requests by choosing the best inten...
04/30/2020 ∙ by Raviteja Anantha, et al. ∙ 0 ∙ share

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Finding Experts in Transformer Models

In this work we study the presence of expert units in pre-trained Transf...
05/15/2020 ∙ by Xavier Suau, et al. ∙ 0 ∙ share

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Variational Neural Machine Translation with Normalizing Flows

Variational Neural Machine Translation (VNMT) is an attractive framework...
05/28/2020 ∙ by Hendra Setiawan, et al. ∙ 0 ∙ share

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Modality Dropout for Improved Performance-driven Talking Faces

We describe our novel deep learning approach for driving animated faces ...
05/27/2020 ∙ by Ahmed Hussen Abdelaziz, et al. ∙ 0 ∙ share

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Collegial Ensembles

Modern neural network performance typically improves as model size incre...
06/13/2020 ∙ by Etai Littwin, et al. ∙ 0 ∙ share

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On the generalization of learning-based 3D reconstruction

State-of-the-art learning-based monocular 3D reconstruction methods lear...
06/27/2020 ∙ by Miguel Angel Bautista, et al. ∙ 0 ∙ share

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